Today, most manufacturing processes require complex industrial machines utilizing rotating or reciprocating elements. The efficient operation and maintenance of these machines is essential to maximizing production and minimizing downtime. When a rotating machine element acquires a defect, that defect is seldom catastrophic at onset. Instead, the defect is usually of a latent or incipient nature, such as a hairline fracture in the tooth of a gear. Notwithstanding a probable reduction in the efficiency of the machine, if such a fault is not detected, isolated, and repaired it could grow into a catastrophic failure of the machine with resultant loss of production and possible injury to personnel. Unfortunately, due to the noise generated by these machines and the acoustic environment in which they normally operate, it is often difficult if not impossible to detect latent or even incipient defects in rotating elements of the machine by visual or aural inspection. Further complicating the detection of such faults is that faulty components may be hidden from view, such as a single gear in an enclosed gearbox.
It is desirable to detect and locate faults while the machine is operating in its normal environment so as not to interfere with the production process. Taking the machine off line to perform predictive maintenance creates an undesirable and inefficient situation, requiring a back-up or redundant machine in order to prevent a shutdown of the production process.
It is known that a defective rotating or reciprocating machine element will generate periodic vibrations as the defect comes into contact with other machine elements along its path of rotation. For example, a roller bearing having a hairline fracture will generate a vibration each time the fracture contacts another machine element, generating a periodic series of vibrations. In U.S. Pat. No. 5,109,700 to Hicho, these periodic vibrations are detected by a vibration transducer attached to the machine. The transducer converts the vibrations into an electrical signal which is filtered to obtain selected frequencies of the electrical signal. The filtered electrical signal is then converted into a frequency spectrum by a fast Fourier transform. Random or spurious components are eliminated leaving only frequency components that are representative of the machine running speed. Corresponding frequency components remaining are averaged, and the highest average amplitude value is used as a bearing condition indicator.
Another prior art approach to detecting faults in rotating machine elements is that disclosed in U.S. Pat. No. 4,007,630 to Noda. Noda describes a device for detecting damage to rotators, such as ball bearings. Mechanical oscillation is converted into an electric signal, and the peak values of this electric signal are detected, retained for a period of time, and reset to zero. The output signal is fed into a smoothing integrator to extract a mean value from which the presence of a rotator fault is determined.
In U.S. Pat. No. 4,931,949 to Hernandez et al., a gear defect analyzing system is disclosed. Signals from an accelerometer and a shaft encoder pass through full wave rectifiers and low pass filters in order to extract the amplitude envelope, which is then converted to a digital signal for analysis by a microcomputer. A Top-Dead-Center pulse (once per shaft revolution pulse) is added to ensure that an encoder pulse was not missed. Time history analysis is performed on the signal, and tooth-to-tooth interaction is recorded until the pattern begins to repeat. Subsequent recordings are averaged with respect to previous records to produce a unique pattern to identify which tooth-to-tooth interaction is likely to involve defective teeth.
A consideration which the prior art fails to account for involves the trade-off that exists between the required sampling rate of a vibration signal and the time record length. Generally, an impact or other event of interest will generate a signal which lasts for only a few milliseconds at best. As a result, the envelope of this signal will only be present for a few milliseconds, typically 5 to 10. A minimum sampling rate in the ten to fifty thousand samples per second range must be employed to capture an event of such short duration, and a typical time record could demand a system capable of storing up to 3,000,000 samples. With a large computer, records of this size can be dealt with, but large computers are generally not very portable and are difficult to use in a typical industrial setting where many machines are periodically monitored for faults. In addition, typical field portable data collectors/analyzers are incapable of handling extremely large time records. Therefore, there is a need for a highly portable fault detection system that is capable of employing existing field portable data collectors while ensuring that events of interest are captured within the time record.
Variations in gear ratios due to "slop" in the gear train are another impediment to accurate vibration analysis. If one is attempting to analyze a rotating element that is buried within a gearbox, it is known to use a shaft speed indicator signal, or tachometer signal, from another shaft in the gear train that is easily accessible and then multiply or divide that tachometer signal by the gear ratio to arrive at a corrected speed representative of the rotating element under analysis. However, there is often considerable slack or slop in most gear trains, and this slop will cause errors in the tachometer signal which will introduce errors when the tachometer signal is synchronously averaged with a vibration signal. This error is particularly amplified where the shaft being monitored by the tachometer is a relatively slowly rotating shaft, and the gear of interest is rotating at a relatively high frequency. In such a case, it is likely that the averaging will totally eliminate the frequencies of interest because the tachometer signal will not be properly synchronized with the high speed gear. Adding to this problem is the natural high frequency signals that are produced by impacting gear teeth. These-high frequency impact signals are the most telling of a cracked tooth, but their high frequency makes them most susceptible to being averaged out during synchronous averaging should the tachometer signal be slightly asynchronous.